Studied by 9 people
Population
the entire group of individuals we want information about
Census
collects data from every individual in the population
Sample
a subset of individuals in the population from which we actually collect data
Bias
if the value you want to know gets underestimated or overestimated
Convenience sample
chooses the individuals easiest to reach; results in bias
Voluntary response
sample consists of people who choose themselves by responding to a general invitation
Simple random sample (SRS)
consists of n individuals from the population chosen in such a way that every set of n individuals has an equal chance to be the sample actually selected
Table of random digits
where each entry is equally likely to be any of the 10 digits 0 through 9 and the entries of independent of each other
Choosing and SRS
Label each individual in the population numerically and use the Table to select labels at random
Stratified random sample
classify the population into groups of similar individuals called strata, then choose a separate SRS in each stratum and combine to form the sample
Cluster sample
classify the population of groups of individual located near each other, then choose and SRS of the clusters, and all the individuals in the chosen clusters are included in the sample
Under coverage
occurs when some members of the population cannot be chosen in a sample
Nonresponse
occurs when an individual chosen for the sample can’t be contacted or refuses to participate
Response bias
a systematic pattern of incorrect responses in a sample survey
Wording of questions
the most important influence on the answers given to s
Observational study
observes individuals and measures variables of interest but does not attempt to influence the responses
Experiment
imposes some treatment on individuals to measure their responses; cause and effect
Confounding
occurs when two variables are associated in such a way that their effects on a response variable cannot be distinguished from each other
Treatment
a specific condition applied to the individual in an experiment
Experimental units
the smallest collection of individual to which treatments are applied
Subjects
when the units are human beings
Principles of Experimental Design
Comparison - design compares 2 or more treatments
Random assignment - assign experimental units to treatment to balance the effects of confounding variables
Control - keep other variables the same for all groups
Replication - use enough units that differences in the effects of the treatments can be distinguished from ones between the groups
Statistically significant
an observed effect so large it would rarely occur by chance
Completely randomized design
treatments are assigned to all experimental units by chance
Control group
receives an inactive treatment or existing baseline treatment
Placebo effect
response to dummy treatment
Double-blind experiment
neither the subjects nor those who interact with them and measure the response variable know which treatment a subject received
Block
a group of experimental units that are known before the experiment to be similar in some way that is expected to affect the response to treatments
Randomized block design
the random assignment of experimental units to treatments is carried out separately within each block
Matched pairs design
each block consists of a matching pair of similar experimental units
Note 
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